{
 "cells": [
  {
   "cell_type": "markdown",
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   "source": [
    "# Ising Model\n",
    "\n",
    "The Ising model is an important physical model, which manifest in various applications. Originally, the model was formulated to reflect interactions between magnetic dipole moments of atomic spins in lattices but since, it was found relevant to describe many systems, such as genetic markers[1], superconducting layered compounds[2], Majorana fermions[3], voter model[4].\n",
    "\n",
    "The Ising model is essentially a second order interaction Hamiltonian, which describes the state of the system according to the Hamiltonian ground state and thermodynamical properties. As such, the Ising model is also an example of Quadratic unconstrained binary optimization (QUBO) and thus can be mapped to solve NP hard problem. For example, one can equivalently formulated a graph maximum cut (Max-Cut) to an Ising model.\n",
    "\n",
    "Using Classiq's platform, we hereby demonstrate how to formulate the Ising model into an optimization problem, which will be sent to solution using Classiq's quantum approximated optimization algorithm (QAOA). The results of the model are obtained using execution of a quantum simulator, and can be similarly redirected to execution using other simulators or even quantum hardware (see [5] for execution options)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4f19f49-8eda-4505-ad82-9db5b6f317c1",
   "metadata": {},
   "source": [
    "## 0. Pre-requirments\n",
    "\n",
    "The model is using several Classiq's libraries in addition to basic python tools."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c6bb59fb-285b-439d-871e-7952c2df8db2",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2024-05-07T15:22:54.375173Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pyomo.core as pyo"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87467107-a15a-4eab-8931-c4d0f32559d1",
   "metadata": {},
   "source": [
    "## 1. Define the Optimization Problem\n",
    "\n",
    "We created a python pyomo model to describe an Ising model as optimization problem over the configuration of spins. We take a simple manifestation of the 1d Ising model, described as [6]:\n",
    "\n",
    "$H(\\sigma) = -\\sum\\limits _{i,j}J\\sigma_{i}\\sigma_{j}-\\sum\\limits _{i} h\\sigma_{i}$\n",
    "\n",
    "where for any two adjacent sites $i, j$ there is an interaction $J$, and for any site $i$ there is a contribution of magnetic field $h$. Here, $\\sigma$ represent the spin's value, it is discrete and can have value within the set of ${-1,1}$. We use transformation of $\\sigma \\rightarrow (2*z-1)$, where $z$ is a binary variable.\n",
    "\n",
    "An option for periodic boundary condition for the 1d spin structure is embedded in the model, which declares whether the first and last spins are interacting in the model (i.e., whether the spin configuration is of closed chain, or open line)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "37e95f02-075e-45f6-94f1-6951ea81b0a4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:22:54.381762Z",
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   "source": [
    "def ising_model_1d(J: int, h: int, n: int, periodic: str) -> pyo.ConcreteModel:\n",
    "    model = pyo.ConcreteModel(\"ising\")\n",
    "\n",
    "    # Define the variables:\n",
    "    model.z = pyo.Var(range(n), domain=pyo.Binary)\n",
    "    z_array = np.array(list(model.z.values()))\n",
    "\n",
    "    E = lambda i, j: -J * (2 * z_array[i] - 1) * (2 * z_array[j] - 1) - (h / 2) * (\n",
    "        (2 * z_array[i] - 1) + (2 * z_array[j] - 1)\n",
    "    )\n",
    "\n",
    "    # create the ising Hamiltonian\n",
    "    if periodic == \"True\":\n",
    "        model.H = E(0, n - 1)\n",
    "    if periodic == \"False\":\n",
    "        model.H = -(h / 2) * ((2 * z_array[0] - 1) + (2 * z_array[n - 1] - 1))\n",
    "    for i in range(n - 1):\n",
    "        model.H = model.H + E(i, i + 1)\n",
    "\n",
    "    # setting the objective:\n",
    "    model.cost = pyo.Objective(expr=model.H, sense=pyo.minimize)\n",
    "\n",
    "    return model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e00dbb0-2d79-4f3c-a765-dca0ea111505",
   "metadata": {},
   "source": [
    "## 2. Create your Ising model\n",
    "\n",
    "The user choses what parameters of interaction coupling $J$ and magnetic field $h$ to insert, in addition to whether the boundry conditions are periodic."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c053de5b-bbb4-4c8e-b86a-840d792c407f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:22:54.394509Z",
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    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "ising_model = ising_model_1d(J=10, h=-20, n=6, periodic=\"True\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "098444e8-c93f-42a8-aeeb-5a13e039565a",
   "metadata": {
    "tags": []
   },
   "source": [
    "## 3. Optimize Using to Quantum Optimization Algorithm\n",
    "\n",
    "We will now create a QAOA model for the optimization problem. The results of the model is the sequance of qubit values giving the minimized energy for the protein. In order to optimize the results, we recommend the user to explore the number of repatitions for the model (`num_layers`) and the number of iterations for the optimizer (`max_iteration`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0cad145c-b78a-4c9e-945a-fffb7e4fef45",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:22:54.404600Z",
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     "shell.execute_reply": "2024-05-07T15:22:57.262051Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from classiq import construct_combinatorial_optimization_model\n",
    "from classiq.applications.combinatorial_optimization import OptimizerConfig, QAOAConfig\n",
    "\n",
    "qaoa_config = QAOAConfig(num_layers=5)\n",
    "\n",
    "optimizer_config = OptimizerConfig(\n",
    "    max_iteration=100,\n",
    "    alpha_cvar=0.7,\n",
    ")\n",
    "\n",
    "qmod = construct_combinatorial_optimization_model(\n",
    "    pyo_model=ising_model,\n",
    "    qaoa_config=qaoa_config,\n",
    "    optimizer_config=optimizer_config,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae3233b3-9805-4c8a-b115-d4fa9defcd92",
   "metadata": {},
   "source": [
    "We also set the quantum backend we want to execute on:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4f779a6a-dae4-4235-92be-f90820fbfbeb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:22:57.280659Z",
     "iopub.status.busy": "2024-05-07T15:22:57.280120Z",
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     "shell.execute_reply": "2024-05-07T15:22:57.305665Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from classiq import set_execution_preferences\n",
    "from classiq.execution import ClassiqBackendPreferences, ExecutionPreferences\n",
    "\n",
    "backend_preferences = ExecutionPreferences(\n",
    "    backend_preferences=ClassiqBackendPreferences(backend_name=\"aer_simulator\")\n",
    ")\n",
    "\n",
    "qmod = set_execution_preferences(qmod, backend_preferences)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2425da2e-35c9-49a7-8479-c1856ee34f75",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:22:57.312667Z",
     "iopub.status.busy": "2024-05-07T15:22:57.312406Z",
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     "shell.execute_reply": "2024-05-07T15:22:57.343993Z"
    }
   },
   "outputs": [],
   "source": [
    "from classiq import write_qmod\n",
    "\n",
    "write_qmod(qmod, \"ising_model\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f476b81-ce50-4cc5-a8d7-13c7b5033e0e",
   "metadata": {},
   "source": [
    "Now we can create a quantum circuit using the `synthesize` command and show it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0b28f2dc-26ec-4975-9e1f-41adfdd75cb4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:22:57.347982Z",
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     "shell.execute_reply": "2024-05-07T15:23:01.962520Z"
    },
    "pycharm": {
     "name": "#%%\n"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opening: https://platform.classiq.io/circuit/e1a07618-2899-4a95-9d21-8eeb100cb053?version=0.41.0.dev39%2B79c8fd0855\n"
     ]
    }
   ],
   "source": [
    "from classiq import show, synthesize\n",
    "\n",
    "qprog = synthesize(qmod)\n",
    "show(qprog)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ce840ba-1d3e-461c-99f2-5045d8cb8e29",
   "metadata": {},
   "source": [
    "We now solve the problem by calling the `execute` function on the quantum program we have generated:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6daf89c6-2e5c-41b5-b162-dfd048014919",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:23:01.965793Z",
     "iopub.status.busy": "2024-05-07T15:23:01.965322Z",
     "iopub.status.idle": "2024-05-07T15:23:09.428158Z",
     "shell.execute_reply": "2024-05-07T15:23:09.427541Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from classiq import execute\n",
    "\n",
    "res = execute(qprog).result()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8bbd9d65-d489-40c0-9247-62ebfb5b0f57",
   "metadata": {},
   "source": [
    "We can check the convergence of the run:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "370e71c6-764e-4296-882a-d5daa14d3176",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2024-05-07T15:23:09.457962Z"
    },
    "tags": []
   },
   "outputs": [
    {
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",
      "text/plain": [
       "<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=640x480>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from classiq.execution import VQESolverResult\n",
    "\n",
    "vqe_result = res[0].value\n",
    "vqe_result.convergence_graph"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f3a4b15-136a-4de1-9fa3-a3fcf23d23cd",
   "metadata": {},
   "source": [
    "## 4. Present Quantum Results\n",
    "\n",
    "We hereby present the optimization results. Since this is a quantum solution with probabilistic results, there is a defined probability for each result to be obtained by a measurement (presented by an histogram), where the solution is chosen to be the most probable one.\n",
    "\n",
    "We remind that in the notation of the solution \"0\" indicate \"-1\" spin value, and \"1\" indicates \"1\" spin value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "da738964-b1ba-4b94-997a-ae7a46254f6c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:23:09.461338Z",
     "iopub.status.busy": "2024-05-07T15:23:09.460808Z",
     "iopub.status.idle": "2024-05-07T15:23:09.487645Z",
     "shell.execute_reply": "2024-05-07T15:23:09.487039Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>probability</th>\n",
       "      <th>cost</th>\n",
       "      <th>solution</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.189</td>\n",
       "      <td>-180.0</td>\n",
       "      <td>[0, 0, 0, 0, 0, 0]</td>\n",
       "      <td>189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.033</td>\n",
       "      <td>-100.0</td>\n",
       "      <td>[0, 0, 1, 0, 0, 0]</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.032</td>\n",
       "      <td>-100.0</td>\n",
       "      <td>[0, 1, 0, 0, 0, 0]</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.030</td>\n",
       "      <td>-100.0</td>\n",
       "      <td>[0, 0, 0, 0, 0, 1]</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.030</td>\n",
       "      <td>-100.0</td>\n",
       "      <td>[0, 0, 0, 0, 1, 0]</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    probability   cost            solution  count\n",
       "0         0.189 -180.0  [0, 0, 0, 0, 0, 0]    189\n",
       "7         0.033 -100.0  [0, 0, 1, 0, 0, 0]     33\n",
       "8         0.032 -100.0  [0, 1, 0, 0, 0, 0]     32\n",
       "9         0.030 -100.0  [0, 0, 0, 0, 0, 1]     30\n",
       "10        0.030 -100.0  [0, 0, 0, 0, 1, 0]     30"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "from classiq.applications.combinatorial_optimization import (\n",
    "    get_optimization_solution_from_pyo,\n",
    ")\n",
    "\n",
    "solution = get_optimization_solution_from_pyo(\n",
    "    ising_model, vqe_result=vqe_result, penalty_energy=qaoa_config.penalty_energy\n",
    ")\n",
    "optimization_result = pd.DataFrame.from_records(solution)\n",
    "optimization_result.sort_values(by=\"cost\", ascending=True).head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "81d6f1dd-7e65-4118-bc8b-9ee662c72a68",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T15:23:09.490132Z",
     "iopub.status.busy": "2024-05-07T15:23:09.489947Z",
     "iopub.status.idle": "2024-05-07T15:23:09.702616Z",
     "shell.execute_reply": "2024-05-07T15:23:09.701922Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<Axes: title={'center': 'cost'}>]], dtype=object)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "optimization_result.hist(\"cost\", weights=optimization_result[\"probability\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6245acd-981b-48a7-82b1-2585ef752666",
   "metadata": {},
   "source": [
    "## References\n",
    "\n",
    "[1] The Ising model in physics and statistical genetics, J. Majewski, H. Li, J. Ott.\n",
    "\n",
    "[2] A short introduction to topological quantum computation, Ville T. Lahtinen and Jiannis K. Pachos.\n",
    "\n",
    "[3] Recent progresses in two-dimensional Ising superconductivity, W. Li et al.\n",
    "\n",
    "[4] Phase transition and power-law coarsening in Ising-doped voter model, Adam Lipowski, Dorota Lipowska, Antonio L. Ferreira.\n",
    "\n",
    "[5] Classiq's user guide, execution options: https://docs.classiq.io/latest/reference-manual/executor/\n",
    "\n",
    "[6] The Ising model in wikepidia https://en.wikipedia.org/wiki/Ising_model"
   ]
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